Mapping home internet activity during COVID-19 lockdown to identify occupation related inequalities

Sci Rep. 2021 Oct 26;11(1):21054. doi: 10.1038/s41598-021-00553-7.

Abstract

During the COVID-19 pandemic, evidence has accumulated that movement restrictions enacted to combat virus spread produce disparate consequences along socioeconomic lines. We investigate the hypothesis that people engaged in financially secure employment are better able to adhere to mobility restrictions, due to occupational factors that link the capacity for flexible work arrangements to income security. We use high-resolution spatial data on household internet traffic as a surrogate for adaptation to home-based work, together with the geographical clustering of occupation types, to investigate the relationship between occupational factors and increased internet traffic during work hours under lockdown in two Australian cities. By testing our hypothesis based on the observed trends, and exploring demographic factors associated with divergences from our hypothesis, we are left with a picture of unequal impact dominated by two major influences: the types of occupations in which people are engaged, and the composition of households and families. During lockdown, increased internet traffic was correlated with income security and, when school activity was conducted remotely, to the proportion of families with children. Our findings suggest that response planning and provision of social and economic support for residents within lockdown areas should explicitly account for income security and household structure. Overall, the results we present contribute to the emerging picture of the impacts of COVID-19 on human behaviour, and will help policy makers to understand the balance between public health and social impact in making decisions about mitigation policies.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Australia
  • COVID-19 / epidemiology*
  • COVID-19 / prevention & control*
  • Communicable Disease Control
  • Employment
  • Environment
  • Family Characteristics
  • Geography
  • Humans
  • Income
  • Internet*
  • Occupations
  • Policy
  • Quarantine*
  • Risk Factors
  • SARS-CoV-2
  • Socioeconomic Factors*